Price history
Recorded standalone sale prices and the latest available store price, in USD. Historical dots use the sale start date and its recorded offer price. Prices can change during a sale; this is not a daily price log. Bundle prices and upcoming offers are excluded. History covers up to the 100 most recent recorded offers.
Lowest recorded standalone price in this history: FREE. The latest store price is FREE, matching the lowest recorded price shown here.
View 2 recorded prices
| Sale start / price check | Price | Observation |
|---|---|---|
| FREE | Latest store price | |
| FREE | Unity First Price 2026-06-20 2026-06-27 |
Sale and bundle history
The 1 most recent recorded offers including this asset. Past offers may no longer be available. Bundle prices cover a package, not this asset alone.
About Local Voice LLM
LocalVoiceLLM brings together several of my other assets: SimpleOfflineSTT (Speech Recognition), SimpleOfflineLLM (AI agent) and SimpleOfflineTTS (Text-to-Speech) to create a completely local, offline, clean interface for creating a dialogue with a Large Language Model. It's completely offline without any networking or services required.
It does not have any platform-specific code or libraries, so can in theory be used on any platform supported by the Inference package - although memory requirements for running so much through Unity Inference can get high, and desktop and high-end mobile platforms are recommended. Tested on Windows, Android, MacOS and Web using WebGPU.
Please be aware that separate purchases are required for full functionality. You will need at least SimpleOfflineLLM to get Large Language Model support, and either SimpleOfflineSTT (speech recognition) and/or SimpleOfflineTTS (text-to-speech) for the voice interface.
The deployment sizes for several full-precision models can become large, so it's recommended to use uint8 quantized versions to decrease the model sizes to approximately one quarter. With a small (SmolLM2) LLM model, and quantized ONNXs, you can deploy the full system in approximately 350MB.
It does not have any platform-specific code or libraries, so can in theory be used on any platform supported by the Inference package - although memory requirements for running so much through Unity Inference can get high, and desktop and high-end mobile platforms are recommended. Tested on Windows, Android, MacOS and Web using WebGPU.
Please be aware that separate purchases are required for full functionality. You will need at least SimpleOfflineLLM to get Large Language Model support, and either SimpleOfflineSTT (speech recognition) and/or SimpleOfflineTTS (text-to-speech) for the voice interface.
The deployment sizes for several full-precision models can become large, so it's recommended to use uint8 quantized versions to decrease the model sizes to approximately one quarter. With a small (SmolLM2) LLM model, and quantized ONNXs, you can deploy the full system in approximately 350MB.